code: def test_rescaler_on_hammersley() -> None:
      np.random.seed(12)
      sampler = sequences.HammersleySampler(
          dimension=3, budget=4, scrambling=True
      )
      samples = list(sampler)
      sampler.reinitialize()
      samples2 = list(sampler)
      sampler.reinitialize()
      np.testing.assert_array_equal(
          samples, samples2, "Not repeatable"  # type: ignore
      )  # test repeatability of hammersley first
      rescaler = sequences.Rescaler(sampler)
      sampler.reinitialize()
      rescaled_samples = [rescaler.apply(x) for x in sampler]
      expected = [
          [1e-15, 0.600, 0.667],
          [0.333, 0.200, 0.167],
          [0.667, 1.0, 1e-15],
          [1.0, 1e-15, 1.0],
      ]
      np.testing.assert_almost_equal(
          rescaled_samples, expected, decimal=3
      )
  
file_path: nevergrad/nevergrad/optimization/test_sequences.py
imports: import typing
  import numpy
  from ..common import testing
  from .None import sequences
  from .sequences import samplers
label_desc: Use image node_id 6 for calling a global function with example usage: test_rescaler_on_hammersley() without return types